TY - GEN
T1 - Testing and evaluating the single objective intelligent evolutionary algorithm through a graphic interface
AU - Montiel, O.
AU - Sepúlveda, R.
AU - Castillo, O.
AU - Soto, O.
PY - 2007
Y1 - 2007
N2 - The Human Evolutionary Model is an intelligent global optimization method conceived to perform Single and Multiple Objective Optimization, this general method is still in development, especially the Multi Objective (MO) part is being improved. The Single Objective (SO) part has demonstrated that outperforms several algorithms that are in the state of the art, for example Differential Evolution (DE), Particle Swarm Optimizer, and others, we called this part Single Objective Intelligent Evolutionary Algorithm (SO-IEA). The SO-IEA uses Mediative Fuzzy Logic (MFL) for handling doubtful and contradictory information from experts to calculate the appropriated amount of individuals to create and/or to eliminate. MFL is an extension of traditional fuzzy logic and includes Intuitionlstic Fuzzy Logic (IFL) in the Atanassov sense. In this work, we are presenting the algorithm's architecture, experimental results, and a graphical interface that will help to handle the required parameters to use the SO-IEA.
AB - The Human Evolutionary Model is an intelligent global optimization method conceived to perform Single and Multiple Objective Optimization, this general method is still in development, especially the Multi Objective (MO) part is being improved. The Single Objective (SO) part has demonstrated that outperforms several algorithms that are in the state of the art, for example Differential Evolution (DE), Particle Swarm Optimizer, and others, we called this part Single Objective Intelligent Evolutionary Algorithm (SO-IEA). The SO-IEA uses Mediative Fuzzy Logic (MFL) for handling doubtful and contradictory information from experts to calculate the appropriated amount of individuals to create and/or to eliminate. MFL is an extension of traditional fuzzy logic and includes Intuitionlstic Fuzzy Logic (IFL) in the Atanassov sense. In this work, we are presenting the algorithm's architecture, experimental results, and a graphical interface that will help to handle the required parameters to use the SO-IEA.
UR - http://www.scopus.com/inward/record.url?scp=35148845615&partnerID=8YFLogxK
U2 - 10.1109/NAFIPS.2007.383910
DO - 10.1109/NAFIPS.2007.383910
M3 - Contribución a la conferencia
AN - SCOPUS:35148845615
SN - 1424412145
SN - 9781424412143
T3 - Annual Conference of the North American Fuzzy Information Processing Society - NAFIPS
SP - 610
EP - 615
BT - NAFIPS 2007
T2 - NAFIPS 2007: 2007 Annual Meeting of the North American Fuzzy Information Processing Society
Y2 - 24 June 2007 through 27 June 2007
ER -